Integration of Probabilistic Effectiveness with a Two-stage Genetic Algorithm Methodology to Develop Optimum Maintenance Strategies for Bridges

Abstract

reventative Maintenance (PM) measures can be used to postpone/delay the initiation of corrosion from chloride attack in reinforced concrete bridges. However there are a lot of uncertainties that influence their degree of effectiveness. Also the time-application of these measures can raise a conflict between safety requirements and budgets. This paper presents a stochastic approach for estimating the effectiveness of different PM measures. Additionally a two-stage optimisation methodology using the principles of Genetic Algorithms (GA) is developed to address the problem of the timeapplication by linking the effectiveness with the cost to produce optimum PM strategies. Futhermore, the role of the presented time-dependent probabilistic approach in the proposed two-stage GA methodology for obtaining optimum PM strategies is demonstrated.